THE LOUISIANA STATEWIDE LIDAR PROJECT

Robert Cunningham, RS/GIS Coordinator Natural Systems Modeling Group

School of the Coast and Environment Louisiana State University

rcunnin@lsu.edu

David Gisclair, Technical Assistance Program Director Louisiana Oil Spill Coordinators Office

Office of the Governor dgisclair@losco.state.la.us

John Craig, Director of Remote Sensing and R&D Applications 3001 Inc., The Spatial Data Company

jcraig@gnv.3001data.com ABSTRACT Louisiana’s statewide LIDAR project began in 2000 largely in response to the high per capita and repetitive flood loss rates experienced by the FEMA, National Flood Insurance Program and the private insurance industry in the state. The LIDAR systems being used in the Louisiana project are accurate to 15-30 cm RMSE, depending upon land cover, and will support contours of 1’-2’ vertical map accuracy standards. These accuracies meet FEMA standards for floodplain reevaluation studies and map modernization programs designed to update the Flood Insurance Rate Maps (FIRM). The project is being funded by FEMA with matching funds and deliverables distribution provided by the state of Louisiana. The area of the state is approximately 50,000 sq. mi. encompassing about 3500 quarter quadrangles (3.75-minute DEM tile size). Areas in procurement include all of SE Louisiana and the majority of the coastal zone. The project will proceed in six phases over six years with the first phase (554 quarter quads) and second phase (473 quarter quads) completed in 2003. Over 900, 5-meter DEM data files, 2-foot contours and associated metadata files have been delivered and can be found on the LSU Atlas web site (http://.atlas.lsu.edu). Approximately 550 additional LiDAR QQs are scheduled to be completed in 2004.

INTRODUCTION Begun in 2000, Louisiana’s statewide LIDAR project was initiated in response to the high per capita and repetitive flood loss rates experienced by the FEMA, National Flood Insurance Program and the private insurance industry in the state. LIDAR derived, high-resolution topographic information has been accepted by FEMA as a low cost means to update inaccurate and out of date flood maps. The state sponsor for the project, thus far, has been the Louisiana Oil Spill Coordinators Office (LOSCO), which has managed the project and arranged for state match through legislative action. Oil spill contingency planning and response issues plague all Louisiana parishes requiring critical high resolution topographic information. The Louisiana Office of Emergency Preparedness (OEP) has recently assumed administrative control of the project, largely because of OEP’s direct, official connection with FEMA. Sean Fontenot of OEP manages the fiscal aspect of the project and David Gisclair of LOSCO will continue to ably manage the project technical aspects. It is anticipated that the project will require an additional 3 years to complete. LIDAR is an acronym for LIght Detection And Ranging. LIDAR is a complex system of airborne instruments which employ an (airborne/ground-based GPS, an inertial measurement units [IMU]), and an active laser sensor as the source to measure distances (ranging) and angles to specific and densely spaced points (2-6m) on the ground. The LIDAR systems being used in the Louisiana project are accurate to 15-30 cm RMSE, depending upon land cover, and will support contours of 1’-2’ vertical map accuracy standards. These accuracies meet FEMA standards for floodplain reevaluation studies and map modernization programs designed to update the Flood Insurance Rate Maps (FIRM). Previous flood

insurance studies were largely based upon contours from USGS 7.5-minute quadrangle maps, which are accurate to a 5’ vertical map accuracy standard, and as a result are woefully inadequate for Louisiana’s extensive, low-relief, flood prone areas. LIDAR offers many advantages and product derivatives, which will be significant for Louisiana’s low relief and remote wetland environments. The laser ranging device is sensitive to 0.3’ elevation change supporting high-resolution hydraulic model applications for flood plain computations in low relief and coastal environments. LIDAR’s first return data provides vegetation and structure heights for environmental, forestry, agriculture and urban modeling applications. In addition, LIDAR provides remote access to Louisiana’s extensive wetland and swamp forest environments, not easily reached by ground survey teams. Rationale There are several issues concerning Louisiana’s unique topographic condition:

• Louisiana’s low, relative relief and vulnerability to rain-induced, coastal, and back-water flooding • State-wide, extreme vulnerability to oil spills (LOSCO) • Highest per capita and repetitive flood loss rate of any state in the nation (FEMA) • Reduction of exposure to public safety risks and private financial and insurance industry losses

resulting from natural or man-made environmental diasters • Need to contribute high resolution data sets to the National Elevation Data Set (NHD) • Emerging homeland security initiatives

Advantages:

• Relatively low-cost alternative to photogrammetrically derived contour maps • Avoids administrative land access and liability issues prevalent in extensive ground surveys • Remote access in areas of limited ground access due to terrain, vegetative cover or soil conditions

such as Louisiana’s extensive wetlands • Relies on GPS derived heights rather than unreliable local survey control • Ability to monitor high subsidence and structurally unstable areas with multi-temporal surveys

Applications:

• Oil spill contingency planning and response activities • Floodplain reevaluation and restudy • Storm water management • Floodplain mitigation and flood proofing projects • Coastal flooding investigations • Fresh water diversion studies • Coastal restoration projects • Forestry production and monitoring • Land cover and environmental classification • Corridor and right-of-way mapping • Urban modeling: telecommunications, law enforcement, disaster planning and emergency

response

EXAMPLE OF LIDAR UTILIZATION IN LOUISIANA: AMITE BASIN COMMISSION WATERSHED MODELING SYSTEM

High- resolution digital terrain models, derived from LIDAR, provide the basis for a comprehensive, basin-wide hydrologic modeling and management system in the 2000 sq. mi. Amite Basin. The flow diagram below illustrates the system, which is considered a prototype for the management of high-risk floodplain development. The system, currently under development, provides for the engineering reevaluation of floodplains, mitigation planning and improved real-time flood-warnings. Funding support for this initiative includes dedicated taxes for the four affected parishes, FEMA, NWS and USCOE. Louisiana State University (LSU) and the University of Alabama (Huntsville) are involved in R&D efforts. High-

resolution, GPS derived elevation information and associated geodetic control provides the cornerstone for the development of this important program, which will include badly needed standardized benchmarks. Having LIDAR based elevation data allows for application of this watershed model to any basin in Louisiana.

WATERSHED MODEL WATERSHED MODEL –– AMITE RIVER BASINAMITE RIVER BASINSynthetic Storms(s)

EmergencyResponse

Inundation Maps

Terrain Model(DEM’s/LIDAR)

BasinwideHydrologic

Model(s)

Environmental Monitoring FIRMs

BasinwideFloodplain

Management

Algorithm to transpose radar reflectively to quantitative

rainfall distribution

Standardization of Benchmarks

Surveillanceand

Monitoring

WSR-88DWeather Radar

(Slidell, LA)Real Time Event

Simulation

Simulation

Real Time Event

State-wide LIDAR project products:

• xyz point data set (raw, last return) • NED compatible seamless elevation data set (5-meter grid DEM) • 1’-2’ contours and break lines

Funding for state-wide project: Funded areas include all of SE Louisiana, the majority of the coastal zone, Rapides and Calcasieu Parishes. Additional partners may be needed to complete the project. State Lands (LaDOA), LaDEQ, LaDOTD and the two Army Corps Districts appear to be likely candidates. USGS should provide some NED production funds to produce their products. Status: Over 450, 5-meter DEM data files, contours and associated metadata files have been delivered and can be found on the LSU Atlas Web site (http://atlas.lsu.edu). The following status map graphics depicts the planned phases of the project, available and in procurement. 3001 Inc. (3001), a Louisiana based mapping firm, is the contractor for the project. A recognized national leader in digital mapping technologies, 3001 produced the widely used statewide Louisiana CIR DOQQs. 3001 Inc., is now a member of the Watershed VI Alliance for Phase II and future phases of the project.

LA LIDAR PhasesLA LIDAR Phases

LA LIDAR Available as of 20040506 LA LIDAR Available as of 20040506

Yellow Squares = 953 QQsYellow Squares = 953 QQs

LA LIDAR ProcurementLA LIDAR Procurement

Yellow Squares = 951 QQsYellow Squares = 951 QQs

TECHNICAL WORKFLOW: Phase 2 and (likely) future phases of the Louisiana LIDAR Project are being funded and managed under FEMA Region VI contract: EMT-2002-CO-0048 performed by the Watershed VI Alliance partners of Watershed Concepts, 3001,Inc., and ESP Associates. Watershed Concepts is responsible for project management and LIDAR QA/QC. 3001 is responsible for collecting and processing the LIDAR data. ESP Associates is performing the survey QA/QC. LIDAR technology is an efficient means to generate topographic models and contour maps. All LIDAR products delivered meet or exceed National Map Accuracy Standards for DEM (Digital Elevation Model) and contour generation. All data and products associated with contract deliverables will meet or exceed relevant NSSDA and fully comply with the FGDC metadata format standard with the provisions in the contract. The Alliance partners will use Appendix 7, “Digital Product Delivery Specifications,” of these Guidelines as a guide for preparing and submitting deliverables. The FEMA Region VI contract complies with the following: “Guidelines and Specifications for Flood Hazard Mapping Partners”, Appendix 4B. - Airborne Light Detection and Ranging Systems, Federal Emergency Management Agency, February 2002. Guidelines and specifications for LIDAR derived topographic data products have evolved from 1999 to the current 2002 standards in the following areas: RMSE calculation and outliers, obscured areas and data voids, artifact removal, system calibration and verification, land cover classes, breakline requirements, pre and post project deliverables. Currently, a four step process is used in procuring deliverables.

STEP 1: LIDAR DATA ACQUISITION 3001, Inc., utilizes theLeica Geosystems ALS40 LIDAR mapping system to acquire topographical data for the Louisiana project from a variety of aircraft platforms. 3001 was an original partner in the development of the Azimuth Aeroscan Sensor, the predecessor of the ALS 40. The system measures the location (latitude, longitude, and altitude) and attitude (roll, pitch, and heading) of the aircraft and the distance-to-ground and scan angle (with respect to the aircraft fuselage), which allows for determination of a ground position for each impact point of a laser pulse. With this system, the contractor is able to deliver topographic mapping and DEM production from higher altitudes than is possible with most other commercial devices. This is accomplished using a high-powered laser with rapid repetition rates and a narrow pulse width. LIDAR data can be acquired coincident with aerial photography as an efficient means to develop products with high information content. Using LIDAR, the 3001 team is able to produce contours with intervals of 2-foot or less froman altitude of 8,000’. System Specifications System specifications and improvements being deployed for Phase 2 of the project are as follows:

COMPARISON OF LIDAR SYSTEM CAPABILITIES PHASE 1 TO PHASE 2

3 EACH + 3 INTENSITY5 EACH + 0 INTENSITYRETURN CARDS 16’ APART

5 m5 mDEM

2’2’CONTOURS PRODUCED

3’ TO 6’3’ TO 6’HORIZONTAL ACCURACY

0.5’ TO 1’0.5’ TO 1’VERTICALACCURACY

6020QQ PRODUCED/MONTH

8.5 MILLION3.6 MILLIONPOINTS PER QQ

3 m4 mPOINT SPACING

8,000’8,000’AIRCRAFT HEIGHT AGL

30,00015,000PULSES PER SECOND

40º AND 30%55º AND 30%F.O.V. AND OVERLAP

PHASE 2PHASE 1CHARACTERISTIC

LIDAR System Calibration 3001, Inc. submits evidence that the total LIDAR system was calibrated prior to project initiation as well as daily with ELVIS software for the purposes of identifying and correcting systematic errors. Proper system calibration requires repetitive overflight of terrain features of known and documented size and elevation using flight paths similar to those that will be used in the planned flight study acquisition area. Survey personnel, aircraft personnel, and aircraft are mobilized to an appropriate airport in the vicinity of the target acquisition area. Survey personnel capture ground control points using the flight plans as a guide. Meanwhile the aircraft personnel calibrate the LIDAR device by flying the airport area several times, verifying the accuracy of the device through verification of the location of known features that are captured upon arrival by the survey personnel. Such items may include building edges, elevations, pavement edges, runway markers, etc. Once control is established in the field and the LIDAR unit is calibrated, flights begin over the target acquisition area.

Flight Planning Planning a flight path that considers all aspects of data collection is critical to the success of the mission. An analysis of the project area, project requirements, topography, proximity to restricted air space, and other factors will determine the flight path configuration. The mission will include parallel flight lines and at least one cross flight line per one-degree block. The spacing between the flight lines will be collected to produce approximately 30% of overlap between swaths. 3001, Inc. checks the Position Dilution of Precision (PDOP) in the study area and documents mission date, time, flight altitude, airspeed, scan angle, scan rate, laser pulse rates, and other information deemed pertinent.

Airborne GPS and Ground Control Stations 3001, Inc. selects GPS base station(s) carefully to ensure reliable differential processing of airborne GPS data. Two GPS base stations are used simultaneously during the mission. Where possible, GPS base stations shall have ellipsoid height to an accuracy of 2 centimeters relative to the Continuously Operating Reference Stations (CORS) or the High Accuracy Reference Network (HARN), both operated by the NGS. The contractor uses a high-quality, dual-frequency GPS receiver and associated antenna at the GPS base stations. Survey Control The results of the flight planning task are used to determine the number and location of surveys required, as well as type of survey (RTK OTF, GPS, or traditional). RTK OTF is used to capture roadways that can be used for control on corridor mapping applications. GPS is used to capture spot elevations and traditional surveys are performed to capture transects. The 3001 team references any available land cover information to determine more precisely the location of control points. Experience in LIDAR and photogrammetric mapping has shown this to be a critical step, because the location of control based solely on the flight line index may not necessarily be the best location in real-world conditions. Should existing control be discovered while developing the project study area map, these existing points will be incorporated into the plan. NGS Data Sheets for Network Control Points The NGS principal information product, the data sheet, combines control-point position and height information in a single format. Data sheets are retrieved directly from the NGS database by specifying a PID (Permanent Identifier), control point name, area, or survey project identifier. Control point information may be formatted in the traditional NGS Data Sheet Format, DSDATA (samples), or in the Spatial Data Transfer Format. The 3001 team provides as a product, data sheets for all NGS monuments used in verification of LIDAR data accuracy. Data Capture As the aircraft follows the flight lines, the LIDAR unit fires up to 30,000 shots per second and each shot may return as many as 3 returns per shot, resulting in a maximum number of 90,000 measurements per second. Data are stored on hot swapped hard drives. Once the aircraft returns, the hard drives are removed from the aircraft and downloaded to a laptop computer on airport grounds. This means if there has been any system failure, such as a hard drive failure, the aircraft can be sent immediately back to the project area for recapture of data.

STEP 2: PRE-PROCESSING Data are then processed through a bore-sight technique, integrated with the airborne GPS and IMU flight logs, and a patch test is performed. The 3001 team performs bore-sight calibration prior to and after every LIDAR mission. The procedures used allow for precise calibration and monitoring of the LIDAR unit and compensate for roll, pitch, and heading through utilization of an IMU. Raw Data Check-in Once received in the office the raw LIDAR data is assembled and distributed to LIDAR data analysts for clipping, filtering, and processing. The elevation data are then examined and compared to known values

and control. Because of the reflective nature of light, it is common for errors to be recorded because of the reflectivity, or lack thereof, from surfaces within the project area. Though a few points within each mission are indeed identified as discrepant, it is an insignificant percentage (usually less than 5%) that is removed from the data. Clipping of Raw Data Data are then converted from binary format to ASCII in x,y,z format with orthometric heights. Multiple flight lines of LIDAR data are assembled together to cover larger areas. Using a pre-established USGS 3.75-minute quarter-quadrangle boundary cross-reference, individual “tiles” of data are clipped out of the larger data set.

Identification of Remote Sensing Data Voids Data voids are areas where LIDAR returns are insufficient to produce an accurate representation of features. Data voids are identified through application of gray-scale values to LIDAR return strength. This identifies those areas where little or no LIDAR return data are present. Typically, these areas are open water bodies. These water bodies are encompassed by breaklines to maintain a uniform slope across them. DEMs include water bodies so that they are continuous with no breaks. Smaller water bodies may be excluded where LIDAR returns define the features adequately. In rare occasions, freshly laid asphalt (where no cars have driven) may yield little or no returns. Breaklines are placed on those roads where this condition occurs, allowing for proper creation of contours. Rooftops with freshly laid tar will also reflect little or no LIDAR pulses, however building roofs are not components of contour or DEM generation.

STEP 3: POST- PROCESSING Creation and utilization of breaklines The FEMA specification for breaklines is derived from ‘Appendix 4B,’ which can be viewed at http://www.fema.gov/mit/tsd/lidar_4b.htm. This specification states that breaklines are to be created for ‘stream centerlines, drainage ditches, tops and bottoms of stream banks, ridge lines, road crowns, levees, bulkheads, road/highway embankments, and selected manmade features that constrict or control the flow of water (e.g., curb lines).’ The FEMA specification for breaklines to be created for elevation data is too global to be accomplished at reasonable time and cost. In many situations the LIDAR is simply too sparse to allow breaklines to be placed without ancillary data, and in other cases, breaklines are simply not necessary because the data points alone already provide an adequate representation of the surface. The 3001 cost/reality based subset of features necessitating breaklines includes: water bodies of sufficient size to be represented by 4-5 LIDAR points in GRID models (at the nominal spacing of the LIDAR data); data gaps in roads/railroads/levees that are elevated on fill thereby creating small dams in floodplains as necessary to bridge those gaps; the toes of overpass embankments; and road/stream intersections where the road has been cut away at a bridge. LIDAR data is usually dense enough so that breaklines are not required to create good surface models. The selected set is essentially only what is necessary to prevent spurious contours across water bodies of significant size, unwanted breaks in narrow profile levee-like features that constrain the flow of water, and misshapen contours in areas where they are most apparent. Lakes, Ponds and Rivers

• Ponds, lakes and reservoirs that exceed approximately 1000 feet/6 = 166.67 feet ~ 50 meters along the major axis. An acre is 204x204 feet so ponds enclosed by breaklines will be on the order of 2/3 of an acre or greater.

• Double-line drainage exceeding 25 meters in width. This is a reasonable number: there would be approximately five GRID (or LIDAR) points across even the smallest drainage captured with double breaklines. Streams vary in width along their course, so the rule of thumb dictates that a double-sided stream breakline should continue until the stream is consistently narrower than 25 meters width.

• Everything that shows up as a water area on a DRG should be considered for breaklines and used as a first guide to candidate features. Orthos should be systematically examined for additional candidate features that may not appear on the DRG.

Railroads/Levees/Roads Railroads/Levees/Roads that are elevated above surrounding land (built up as a crown on fill in a floodplain area) are important features in floodplain modeling because they act as obstructions and dams to the flow of water. When the width of the feature crown is less than the point spacing, the feature is fragile and may exhibit gaps when a LIDAR point doesn’t fall near the feature apex. Breaklines are added as necessary to bridge gap sections in these features. A single breakline is used from start to end point across the gap, then densification of the breakline with additional verticesis applied to improve surface model triangulation (some TIN creation processes will perform this densification automatically). Road Overpasses In the area of the steep drop on an overpass embankment where bridge data points were removed, it might be necessary to add a simple breakline at the toe of the embankment. Roads that pass under an overpass were obscured by the overpass, so they may also benefit from one or more breaklines to bridge their gaps. Filtering and Editing of Raw Data to Remove Cultural and Vegetative Features 3001’s proprietary LIDAR editing software, Editing LIDAR Visual Interactive System (ELVIS), as well as several commercially available software programs are used for removal of vegetation and manmade features. The process will produce a map of the topography. The data will be georeferenced (UTM Zone 15 - Meters) and placed on the NAD 83 (horizontal) and NAVD 88 (vertical) datum. Obstructions and vegetation are removed and the data is closely examined for anomalies during the quality control process. Redundant visual and automated checks are performed to provide the best possible bare ground surface solution.

LIDAR Data are Captured and Processed using Proprietary ELVIS Software

Creation of 5-Meter Grid 3001 utilizes mission-planning software to determine flight height, scan rate, pulse rate, and field of view to develop the optimum shot spacing. Edited data and breaklines are used together to generate a triangular

irregular network (TIN). The TIN is then processed to create a XYZ grid file with 5-meter point spacing. The resulting 5-meter grid is then processed to create a USGS-formatted DEM. Creation of Contours The same 5-meter grid is then used to produce a two-foot contour line file, which will also be converted into a USGS-formatted DLG. Since the contour files will be created from an interpolated surface, they will not adhere to the same QC/QA standards as required for the randomly spaced bare-earth data points. Different software packages produce contours with varying appearances. 3001, Inc. will however verify the completeness and accuracy of the contours through visual and automated checking.

Typical 5 meter DEM with breaklines: Phase I, Louisiana LIDAR Project

STEP 4: QUALITY CONTROL/QUALITY ASSURANCE

RMSE Calculations to Support Vertical Accuracy The Watershed Alliance team follows the Flood Insurance Study guidelines described below established by FEMA for LIDAR mapping. QA/QC of LIDAR-derived data includes reviews of flight alignments and completeness of supporting data (e.g., cross sections, and profiles). 3001 analysts use the root mean square error (RMSE) to estimate both horizontal and vertical accuracy. RMSE is the square root of the average of the set of squared differences between data set coordinate values and coordinate values from an independent source of higher accuracy for identical points. If those differences are normally distributed and average zero, 95 percent of any sufficiently large sample should be less than 1.96 times the RMSE. Therefore 15-cm RMSE is often referred to as "30-cm accuracy at the 95% confidence level." Following that convention, the vertical accuracy of any DEM is defined as 1.96 times the RMSE of linearly interpolated elevations in the DEM, as compared with known elevations from high-accuracy test points. DEMs should have a maximum RMSE of 15 cm that is acceptable for 6’’ inch contour mapping. The 3001 team field verifies the vertical accuracy of this DEM to ensure that the 15-cm RMSE requirement is satisfied for all major land cover categories that predominate within the area being studied. The RMSE calculated from a sample of test points will not be the RMSE of the DEM. The calculated value may be higher or it may be lower than that of the DEM. Confidence in the calculated value increases with the number of test points. If the errors (lack of accuracy) associated with the DEM are normally distributed

and unbiased, the confidence in the calculated RMSE can be determined as a function of sample size. Similarly, the sample RMSE necessary to obtain 95% confidence that the DEM RMSE is less than 15 cm can also be determined as a function of sample size. For each major land cover category, the 3001 team will test a sample of points and show the test points have an RMSE less than where n is the number of test points in the sample.

( )n

nnRMSEsample1326.2115 −−−

≤

3001 analysts select a minimum of 20 test points for each major land cover category identified. Therefore, a minimum of 60 test points must be selected for three (minimum) major land cover categories, 80 test points for four major categories, and so on. Test point consideration must be taken when planning field surveys to gather cross-section data for hydraulic modeling. The 3001 team will select the test points carefully in areas of the highest PDOP to evaluate DEM accuracy under trees and in vegetation representative of the study area. Test points on sloping or irregular terrain be unreasonably affected by the linear interpolation of test points from surrounding DEM points and, therefore, will not be selected. Areas under dense tree canopy or thick vegetation or along shorelines would also not be selected due to limitations of the sensor.

Quality Assurance/Quality Control Checks The Watershed VI Alliance is using ESP Associates to perform the survey QA/QC and Watershed Concepts to perform the hillshade review of the LIDAR and RMSE calculations using the survey information. Quality control checkpoints are being collected and used to evaluate the accuracy of the bare earth DEMs produced from LIDAR. QC checkpoints are being collected in seven possible land cover classes as applicable in the LIDAR delivery areas. QC points are located on flat terrain where a uniform slope is prevalent to ensure no point is within five meters of a breakline or change in slope. When practical, QC checkpoint locations should be established on public, state, or federal owned property.

1. Site selection: In each LIDAR delivery area, a minimum of 20 checkpoints is being surveyed for each of the major vegetation categories representative of the floodplain. Preliminary locations of checkpoints are then determined and set on transects perpendicular to flight lines through each vegetative category.

2. Reconnaissance: Evaluation of the areas to be surveyed is undertaken. Special attention to areas of development and seasonal planting is being given to ensure base data is representative and current.

3. Ground Surveys: QC checkpoints are being surveyed by GPS methods or a combination of GPS and conventional survey methods. All GPS surveys will conform to 5-cm Local Network accuracy per NOAA Technical Memorandum NOS NGS-58 (Version 4.3, Nov.1997). Third order conventional surveys are being used to extend GPS surveys or existing NGS control into areas where GPS is not practical. Monuments selected for differential GPS base stations should have the best available vertical order and stability. If selected monuments are further than 20 km apart, secondary base stations are being established so that the final survey of checkpoints will satisfy NGS-58 requirements for 5-cm accuracy at the 95% confidence level. Alternatively, RTK GPS may be used for survey control provided that each RTK point has double occupation with a minimum 2-hr separation between observations. Geoid 99 will be used to convert GPS ellipsoidal heights to orhthometric heights for each checkpoint, using NAVD 88 vertical datum.

QA/QC review of Task 12 (Calcasieu Parish) The LIDAR point data and breaklines were evaluated by running each tile through the quality control procedure developed and refined by Watershed Concepts consisting of a hillshade review, RMSE calculation and breakline evaluation. Hillshade Review: A hillshade was generated using ArcInfo for each tile and compared against available imagery. Areas within each tile that contained possible artifacts (e.g. vegetation, noise, and structures) were delineated with polygons.

RMSE Calculation: Elevation differences were calculated between the TIN elevations and the field-surveyed points provided by ESP for the associated Task Area. In order to eliminate negative values, the error results were squared. The average was calculated. The RMSE result was calculated by taking the square root of the Average-^2 result. Breakline Review: Using ArcView, the DXF’s were checked for connectivity and elevation continuity between confluences and tile breaks.

REVIEW CONCLUSIONS Of the 98 quarter quad tiles of LIDAR data that Watershed Concepts reviewed, 218 polygons were created where concerns exist in the data (small areas for the size of the data set). These concerns mainly consisted of remaining vegetation between 1 and 5 feet above the obvious bare earth elevation and aggressive editing around man made features such as levees and drainage canals. The RMSE with all checked points (160) is 11.51cm, which is well within the project scope. Most of the minor breakline problems included lines not being broken at confluences and incorrect elevations. Overall the data sets were very detailed and of good quality. References Craig, J., Phillips, H., (2003). LIDAR Technical Workflow, 3001 Inc., Gainesville, FL-USA. Cunningham, R., (2002). Elevation and Bathymetry Data Profiles, Louisiana I-Teams document for the Governors Office and FGDC, Louisiana State University, Baton Rouge, LA-USA. Edelman, S., (2002), Topographic Data Development for Phase II of the Louisiana LIDAR Project, Watershed VI Alliance Proposal no. 92799 for FEMA Region VI, Watershed Concepts Inc., Cary, NC-USA. Edelman, S., (2003), Phase II Louisiana LIDAR Project, Quality Control Evaluation of LIDAR Data for Calcasieu Parish- Task Area 12, Watershed Concepts Inc., Cary, NC-USA.